Biological sex-specific differences in complex diseases are difficult to study because transcriptomic differences between sexes conflate pre-existing baseline differences in gene regulation and genuine disease-specific responses that differ by sex. Standard between-sex differential expression cannot separate these components, making it impossible to determine whether observed differences are driven by baseline sex differences, disease-specific responses or their interaction. To assess genuine sex differences in disease biology, we developed a framework modelling the sex-by-disease interaction term, which decomposes gene-level expression into baseline sex effects, within-sex disease effects and interaction effects.

We apply this framework to whole blood RNA-seq data from a publicly available cohort of ankylosing spondylitis (AS) patients and healthy controls. AS is a chronic inflammatory arthritis of the axial skeleton with well-documented sex differences in presentation and outcome, yet existing studies have relied on direct between-sex comparisons, leaving the question of how disease biology itself differs by sex largely unaddressed.

Fitting our biological sex-aware interaction model, we distinguish transcriptomic sex differences that are present at baseline from those that arise specifically in disease, representing genuine interaction effects that would be obscured in a pooled analysis. Pathway enrichment analysis within the framework further identified disease-relevant processes offering potential mechanistic explanations for open questions in AS pathogenesis that have not previously been explored.

In summary, we present the first application of a biological sex-aware interaction model to AS transcriptomic data, demonstrating that it captures sex-specific disease signals and mechanistic insights that standard differential expression approaches would miss.

Co-authors: Nikolaus Fortelny, Natalia Nunes